Full-Stack AI Engineer
Posted:
Company Details
Name:Pavago
Industry:
Consulting
Website:
https://www.pavago.co/
Description:
Pavago connecting businesses with top talent, streamlining hiring processes, and providing comprehensive support for long-term success.
Job Details
Job Type:
Full Time
Workplace Type:
On-site
Qualification:
Diploma
Job Experience:
Mandatory
Job Location:
Nairobi County, Kenya
Closing Date:
Undisclosed
Salary:
KES Unspecified / month
Other Pay:
Benefits
Job Category:
Telecommunications
Job Description
Job Title: AI Application Engineer
What You’ll Own
AI Application Development
- Build and deploy AI-powered applications using modern software engineering best practices.
- Integrate LLMs and machine learning models into production environments.
- Develop intelligent features including:
- AI chatbots
- Semantic search
- Document intelligence
- AI copilots
- Workflow automation
- Build scalable APIs that expose AI capabilities to applications.
LLMs, RAG & AI Integration
- Integrate models using:
- OpenAI
- Hugging Face
- PyTorch
- TensorFlow
- Build Retrieval-Augmented Generation (RAG) pipelines.
- Implement semantic search using vector databases including:
- Pinecone
- Weaviate
- FAISS
- ChromaDB
- Optimize prompt engineering and inference workflows.
- Monitor model accuracy, latency, and production performance.
Data Engineering & AI Pipelines
- Build ETL pipelines for structured and unstructured data.
- Automate:
- Data ingestion
- Cleaning
- Validation
- Versioning
- Manage workflows using:
- Airflow
- Prefect
- Dagster
- Work with cloud data warehouses including:
- BigQuery
- Snowflake
- Amazon Redshift
- Optimize pipelines for scalability and cost efficiency.
Full-Stack Development
- Build modern user interfaces using:
- React
- Next.js
- Vue.js
- Develop scalable backend services using:
- Python
- FastAPI
- Flask
- Node.js
- Build APIs that support high-performance AI workloads.
- Ensure applications remain responsive, secure, and production-ready.
Infrastructure, DevOps & MLOps
- Deploy applications using:
- Docker
- Kubernetes
- Build CI/CD pipelines for both applications and AI models.
- Monitor infrastructure using:
- MLflow
- Weights & Biases
- Datadog
- Prometheus
- Improve:
- Inference latency
- Infrastructure reliability
- Deployment automation
- Cloud cost optimization
Security & Compliance
- Build secure AI systems using modern authentication and authorization practices.
- Protect sensitive business and customer data.
- Support compliance with:
- GDPR
- HIPAA
- SOC 2
- Implement API security, rate limiting, and access controls.
Must-Have Qualifications
Experience
- 3+ years of software engineering experience with exposure to AI/ML systems.
- Experience building production AI applications.
- Experience deploying machine learning models into production environments.
Core Skills
- Strong proficiency in:
- Python
- JavaScript / TypeScript
- Hands-on experience with:
- OpenAI APIs
- Hugging Face
- PyTorch
- TensorFlow
- Experience building scalable REST APIs.
- Front-end development experience with:
- React
- Next.js
- Vue.js
- Strong SQL skills and experience working with cloud databases.
Additional Requirements
- Experience using:
- Docker
- Kubernetes
- CI/CD pipelines
- Familiarity with vector databases and AI inference services.
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